Data Engineer at Miva Open University

Miva Open University is a Pan-African Open Distance e-Learning University that is committed to enabling learners reach their maximum potential by delivering top-tier tertiary education services through the use of high-quality content and immersive practical experiences.

OVERALL FUNCTION

• We are seeking a skilled Data Engineer to design, build, and maintain the data infrastructure powering Miva’s digital learning products, AI models, and analytics platforms.
• You’ll play a key role in shaping a data-first, AI-ready culture in a fast-growing edtech company.
• This role involves close collaboration with data scientists, ML engineers, and product teams to develop real-time pipelines, support AI/ML workloads, and ensure the availability of clean, structured, and trustworthy data for both operational and strategic use.

KEY RESPONSIBILITIES

• Design, implement, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion, transformation, and storage across internal and external systems.
• Build and optimize data architectures to support high-throughput analytics, AI/ML pipelines, and embedded intelligence in digital products.
• Develop and maintain feature stores and curated datasets for training and inference across machine learning models.
• Integrate and manage vector databases and data stores optimized for LLM (Large Language Model) embeddings and semantic search.
• Support real-time data pipelines for model inference and personalization, ensuring low-latency data availability.
• Monitor and manage data drift and data quality to maintain integrity across production ML systems.
• Collaborate with data scientists, ML engineers, and analysts to understand data needs, define interfaces, and facilitate rapid experimentation.
• Implement data governance practices, including metadata management, access control, lineage tracking, and data cataloging.
• Enforce data security and privacy standards aligned with relevant policies and regulations (e.g., GDPR.
• Document all pipelines, infrastructure, and workflows for transparency and operational continuity.
• Continuously evaluate and recommend improvements in tooling and architecture to improve performance, observability, and scalability.

QUALIFICATIONS AND SKILLS

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 4+ years of experience in data engineering or a similar role, with proven experience supporting machine learning or AI systems.
• Proficiency in Python, SQL, and one or more ETL tools or frameworks (e.g., Apache Airflow, dbt, Luigi).
• Experience with cloud data platforms such as AWS (Redshift, S3, Glue), GCP (BigQuery), or Azure (Data Factory, Synapse).
• Strong understanding of relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra).
• Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate, or ChromaDB and their role in LLM-enhanced search and recommendation systems.
• Experience with data warehousing concepts and tools like Snowflake, BigQuery, or Amazon Redshift.
• Knowledge of data modeling, schema design, and performance tuning.
• Familiarity with version control systems (e.g., Git) and CI/CD practices.
• Understanding of data privacy laws and data security best practices.
• Strong problem-solving skills and ability to work independently and in teams.
• Excellent communication skills, with the ability to collaborate across technical and non-technical stakeholders.

Method of Application